Frank E Harrell Jr <[EMAIL PROTECTED]> [Sun, Jul 20, 2008 at 12:20:28AM CEST]:
> Johannes Huesing wrote:
>> Because regulatory bodies demand it?
[...]
>
> And how anyway does this
> relate to predictors in a model?
Not at all; you're correct. I was mixing the topic of this discussion
up with another kind of silliness.
I had a discussion with a biometrician in a pharmaceutical company
though who stated that when you have only one df to spend it will be
better to dichotomise it at a clinically meaningful point than to
include it as a linear term. He kept the discussion on the ground of
laboratory measurements like sodium, where a deviation from normal
ranges is very significant (and unlike, say, cholesterol, where you
have a gradual interpretation of the value). He has a point there, but
in general the reason for sacrificing information is a mixture of
laziness, the preference for presenting data in tables and to keep the
modelling "consistent" with the tables (for instance to assign an odds
ratio to each cell).
--
Johannes Hüsing There is something fascinating about science.
One gets such wholesale returns of conjecture
mailto:[EMAIL PROTECTED] from such a trifling investment of fact.
http://derwisch.wikidot.com (Mark Twain, "Life on the Mississippi")
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